This specification relates to face detection, and specifically to luminance adjusted face detection.
Digital images are being used in increasingly more applications. In many of those applications, automated analysis of digital images can be performed to provide either or both of face detection and face recognition. In face detection, an image region is identified as depicting the face of a human (or other) being. In face recognition, a detected face is identified as corresponding to a specific, known individual. Face detection and face recognition can be used for a wide variety of tasks, including image enhancement, content-based retrieval, automatic identification, and image database management. For instance, in image processing applications, face detection can be used to automatically perform enhancements, such as red-eye correction and contrast adjustment. Further, face recognition can be used in conjunction with search applications that retrieve images depicting a particular individual.
Real-time face detection algorithms include, for example, the Viola-Jones algorithm, have been developed for performing face detection in digital images. The Viola-Jones algorithm searches pixels of a candidate window using multiple classifiers, with each classifier configured to select particular visual features (e.g., eyes, nose, and mouth) from a set of possible visual features. Further, the classifiers are grouped in stages, which are cascaded. As a result, only candidate windows that pass the classifiers of the current stage are submitted for further analysis to the classifiers of a subsequent stage.